deep-neural-network

This paper proposes a Partial Information Decomposition framework to select the most informative pair of MRI contrasts for brain tumor segmentation using lightweight 3D U-Nets, reducing computational cost while maintaining performance.

This paper presents an alternative architecture for LLMs using Radial Basis Function (RBF) networks that eliminates deep neural networks and finds the global optimum in closed form, requiring no iterative training. It also reviews other non-DNN methods like KANs and k-NN retrieval, with a case study demonstrating increased explainability and faster training.